IJCER (www.ijceronline.com) International Journal of computational Engineerin...
Cognitive Radio Spectrum Sensing 1586 ppt
1. Cognitive Radio Spectrum
Sensing
Under the guidance of : Mr. Sandeep Sharma
Designation : Research/Faculty Associate
ANUPAM K YADAV
11/IEC/021
Gautam Buddha University
2. CONTENTS
• Introduction
• Application
• Architecture for CRC Network
• Types of spectrum Sensing
• Energy Detection Mathematical model
• Algorithm Used for Detection of spectrum Holes
• Results and simulations
• References
3. Cognitive Radio : It’s a Radio technique that aims to utilize Radio
Spectrum more efficiently by Intelligently exploiting licensed spectrum.
Need to exploit spectrum :
There is increasing number of smartphones
& laptops every year which have different
QoS requirements :
• Web browsing
• Faster Internet
• Multimedia downloads
5. In CR Network we provide services to all users at same time :
• Use of VACANT bandwidth :
• STs can use those spectrums which are
not occupied by (primary receivers) PRs.
• SHARING of bandwidth :
• STs can share spectrum as long as they do
not interfere with PRs
6. There are two types of Radio resources in CR –Network :
1. Radio resource ( licensed band )RR
Small bandwidth, Hight Tx power, High reliability.
2. Cognitive Radio resource ( Unlicensed Band) CRR
Broad Bandwidth, low Tx Power, low reliability.
Challenge : Is to jointly utilize both the bands to increase system
performance.
7. Non-Cooperative Architecture
(standalone )
There are two different interfaces operating at
licensed and unlicensed band.
• Power limited C-RR is used for Users near the
MACRO Cell BS, while it uses licensed RR for users
who are further away.
• Small Cell they use CRR to cover traffic hotspots
and bridges the coverage gaps.
They offer High capacity
8. Cooperative architecture
Also uses both licensed and CRR .Have longer range
of communication as compared to non cooperative.
• Relay is deployed for better coverage & capacity.
It can communicate with BS using licensed RR &
can provide local coverage using CRR. It works in
duplex way.
• It also uses the Cognitive RR to form Virtual
Antenna Array.
10. Energy Detection mathematical Model
• We calculate energy of receiving signal to find the presence of primary user.
• In spectrum the primary user is present when calculated level of incoming
energy level is more than threshold energy level.
• Also we compare the output of energy detector with a threshold which
depends on noise floor and signal is detected.
• Energy detection is a non-coherent detection technique which do not need
prior knowledge about primary user as required by other filters, so it has
relatively less complexity as compared to other spectrum sensing.
11. Algorithm Used for Detection of spectrum Holes
• In this paper PSD is used for detection of spectrum holes. Here we can
compare values of PSD for different channels and can estimate spectrum
holes.
• PSD is also used for modulation of incoming input signals at different channel
with different carrier frequencies.
• Then this modulated signal is multiplexed where noise may or may not
corrupt the signals. At the receiver end, PSD from different channels is
calculated.
• And lastly, the threshold power level is compared with calculated power for
the presence of primary user.
13. References
• Juan Andrés Bazerque, Georgios B. Giannakis, “Distributed SpectrumSensing For
Cognitive Radio Networks By Exploiting Sparsity”, IEEETransactions On Signal
Processing, Vol. 58, No. 3, March 2010.
• S.Haykin, “Cognitive Radio: Brain-Enpowered Wireless Communications,” IEEE
JSAC, vol. 23, no. 2, Feb. 2005,pp. 201–20.
• Spectrum Sensing for Cognitive Radio. By Simon Haykin, Life Fellow IEEE, David
J. Thomson, Fellow IEEE, and Jeffrey H. Reed, Fellow IEEE
• Takeshi Ikuma and Mort Naraghi-Pour (2008), “A Comparison of Three Classes of
SpectrumSensing Techniques”, IEEE GLOBECOM proceedings.
• F. F. Digham, M. S Alouini and M.K Simon, “On the energy detection of unknown
signals over fading channels”, in Proc. IEEE International Conference on
Communication (ICC003), pp. 3575-3579, May 2003.